Ahmad Firoz

PROCARB: A Database of Known and Modelled Carbohydrate-Binding Protein Structures with Sequence-Based Prediction Tools

Understanding of the three-dimensional structures of proteins that interact with carbohydrates covalently (glycoproteins) as well as noncovalently (protein-carbohydrate complexes) is essential to many biological processes and plays a significant role in normal and disease-associated functions. It is important to have a central repository of knowledge available about these protein-carbohydrate complexes as well as preprocessed data of predicted structures. This can be significantly enhanced by tools de novo which can predict carbohydrate-binding sites for proteins in the absence of structure of experimentally known binding site. PROCARB is an open-access database comprising three independently working components, namely, (i) Core PROCARB module, consisting of three-dimensional structures of protein-carbohydrate complexes taken from Protein Data Bank (PDB), (ii) Homology Models module, consisting of manually developed three-dimensional models of N-linked and O-linked glycoproteins of unknown three-dimensional structure, and (iii) CBS-Pred prediction module, consisting of web servers to predict carbohydrate-binding sites using single sequence or server-generated PSSM. Several precomputed structural and functional properties of complexes are also included in the database for quick analysis. In particular, information about function, secondary structure, solvent accessibility, hydrogen bonds and literature reference, and so forth, is included. In addition, each protein in the database is mapped to Uniprot, Pfam, PDB, and so forth.

Residue propensities, discrimination and binding site prediction of adenine and guanine phosphates.

BackgroundAdenine and guanine phosphates are involved in a number of biological processes such as cell signaling, metabolism and enzymatic cofactor functions. Binding sites in proteins for these ligands are often detected by looking for a previously known motif by alignment based search. This is likely to miss those where a similar binding site has not been previously characterized and when the binding sites do not follow the rule described by predefined motif. Also, it is intriguing how proteins select between adenine and guanine derivative with high specificity.ResultsResidue preferences for AMP, GMP, ADP, GDP, ATP and GTP have been investigated in details with additional comparison with cyclic variants cAMP and cGMP. We also attempt to predict residues interacting with these nucleotides using information derived from local sequence and evolutionary profiles. Results indicate that subtle differences exist between single residue preferences for specific nucleotides and taking neighbor environment and evolutionary context into account, successful models of their binding site prediction can be developed.ConclusionIn this work, we explore how single amino acid propensities for these nucleotides play a role in the affinity and specificity of this set of nucleotides. This is expected to be helpful in identifying novel binding sites for adenine and guanine phosphates, especially when a known binding motif is not detectable.

CDKD: a clinical database of kidney diseases

BackgroundThe main function of the kidneys is to remove waste products and excess water from the blood. Loss of kidney function leads to various health issues, such as anemia, high blood pressure, bone disease, disorders of cholesterol. The main objective of this database system is to store the personal and laboratory investigatory details of patients with kidney disease. The emphasis is on experimental results relevant to quantitative renal physiology, with a particular focus on data relevant for evaluation of parameters in statistical models of renal function.DescriptionClinical database of kidney diseases (CDKD) has been developed with patient confidentiality and data security as a top priority. It can make comparative analysis of one or more parameters of patient’s record and includes the information of about whole range of data including demographics, medical history, laboratory test results, vital signs, personal statistics like age and weight.ConclusionsThe goal of this database is to make kidney-related physiological data easily available to the scientific community and to maintain & retain patient’s record. As a Web based application it permits physician to see, edit and annotate a patient record from anywhere and anytime while maintaining the confidentiality of the personal record. It also allows statistical analysis of all data.

Comparative Analysis of Glycogene Expression in Different Mouse Tissues Using RNA-Seq Data

Glycogenes regulate a wide array of biological processes in the development of organisms as well as different diseases such as cancer, primary open-angle glaucoma, and renal dysfunction. The objective of this study was to explore the role of differentially expressed glycogenes (DEGGs) in three major tissues such as brain, muscle, and liver using mouse RNA-seq data, and we identified 579, 501, and 442 DEGGs for brain versus liver (BvL579), brain versus muscle (BvM501), and liver versus muscle (LvM442) groups. DAVID functional analysis suggested inflammatory response, glycosaminoglycan metabolic process, and protein maturation as the enriched biological processes in BvL579, BvM501, and LvM442, respectively. These DEGGs were then used to construct three interaction networks by using GeneMANIA, from which we detected potential hub genes such as PEMT and HPXN (BvL579), IGF2 and NID2 (BvM501), and STAT6 and FLT1 (LvM442), having the highest degree. Additionally, our community analysis results suggest that the significance of immune system related processes in liver, glycosphingolipid metabolic processes in the development of brain, and the processes such as cell proliferation, adhesion, and growth are important for muscle development. Further studies are required to confirm the role of predicted hub genes as well as the significance of biological processes.

Docking based virtual screening and molecular dynamics study to identify potential monoacylglycerol lipase inhibitors.

Monoacylglycerol lipase (MAGL) is one of the key enzymes of the endocannabinoid system (ECS). It hydrolyzes one of the major endocannabinoid, 2-arachidonoylglycerol (2-AG), an endogenous full agonist at G protein coupled cannabinoid receptors CB1 and CB2. Numerous studies showed that MGL inhibitors are potentially useful for the treatment of pain, inflammation, cancer and CNS disorders. These provocative findings suggested that pharmacological inhibition of MAGL function may confer significant therapeutic benefits. In this study, we presented hybrid ligand and structure-based approaches to obtain a novel set of virtual leads as MAGL inhibitors. The constraints used in this study, were Glide score, binding free energy estimates and ADME properties to screen the ZINC database, containing approximately 21 million compounds. A total of seven virtual hits were obtained, which showed significant binding affinity towards MAGL protein. Ligand, ZINC24092691 was employed in complex form with the protein MAGL, for molecular dynamics simulation study, because of its excellent glide score, binding free energy and ADME properties. The RMSD of ZINC24092691 was observed to stay at 0.1 nm (1 Å) in most of the trajectories, which further confirmed its ability to inhibit the protein MAGL. The hits were then evaluated for their ability to inhibit human MAGL. The compound ZINC24092691 displayed the noteworthy inhibitory activity reducing MAGL activity to 21.15% at 100 nM concentration, with an IC50 value of 10 nM.

ContPro: A web tool for calculating amino acid contact distances in protein from 3D -structures at different distance threshold.

To investigate the functional sites on a protein and the prediction of binding sites (residues)in proteins, it is often required to identify the binding site residues at different distance threshold from protein three dimensional (3D)structures. For the study of a particular protein chain and its interaction with the ligand in complex form, researchers have to parse the output of different available tools or databases for finding binding-site residues. Here we have developed a tool for calculating amino acid contact distances in proteins at different distance threshold from the 3D-structure of the protein. For an input of protein 3D-structure, ContPro can quickly find all binding-site residues in the protein by calculating distances and also allows researchers to select the different distance threshold, protein chain and ligand of interest. Additionally, it can also parse the protein model (in case of multi model protein coordinate file)and the sequence of selected protein chain in Fasta format from the input 3D-structure. The developed tool will be useful for the identification and analysis of binding sites of proteins from 3D-structure at different distance thresholds. Availability It can be accessed at: http://procarb.org/contpro/

Modeling the three-dimensional structures of an unbound single-chain variable fragment (scFv) and its hypothetical complex with a Corynespora cassiicola toxin, cassiicolin

Rubber trees infected with a host-specific cassiicolin toxin often experience considerable leaf fall, which in turn results in loss of crop productivity. It was recently revealed that cassiicolin-specific single-chain variable fragments (scFv) can successfully reduce the toxic effects of cassiicolin. However, the detailed mechanism of antibody action remains poorly understood. The primary sequence of the newly sequenced cassiicolin-specific scFv was highly homologous to several members of single-chain antibodies in the 14B7 family. In this study, with the aid of homology modeling, the three-dimensional structure of cassiicolin-specific scFv was elucidated, and was found to exhibit a characteristic immunoglobulin fold that mainly consists of β sheets. Additionally, molecular docking between the modeled scFv antibody and the available three-dimensional crystal structure of cassiicolin toxin was also performed. The predicted structural complex and the change in accessible surface area between the toxin and the scFv antibody upon complexation reveal the potential role of certain complementarity determining region (CDR) amino acid residues in the formation of the complex. These computational results suggest that mutagenesis experiments that are aimed at validating the model and improving the binding affinity of cassiicolin-specific scFv antibodies for the toxin should be performed.

Identification of hub glycogenes and their nsSNP analysis from mouse RNA-Seq data

Glycogenes regulate a large number of biological processes such as cancer and development. In this work, we created an interaction network of 923 glycogenes to detect potential hubs from different mouse tissues using RNA-Seq data. DAVID functional cluster analysis revealed enrichment of immune response, glycoprotein and cholesterol metabolic processes. We also explored nsSNPs that may modify the expression and function of identified hubs using computational methods. We observe that the number of nsSNPs predicted by any two methods to affect protein function is 4, 7 and 2 for FLT1, NID2 and TNFRSF1B. Residues in the native and mutant proteins were analyzed for solvent accessibility and secondary structure change. Analysis of hubs can help in determining their degree of conservation and understanding their functions in biological processes. The nsSNPs proposed in this work may be further targeted through experimental methods for understanding structural and functional relationships of hub mutants.

Functional annotation and pathway analysis of genes differentially expressed in different stages of Plasmodium falciparum using RNA-Seq Data

Plasmodium falciparum, the deadly protozoan parasite, causes malaria. Malaria remains one of the deadliest infectious diseases in the world. The RNA-Seq data sets were downloaded from NCBI Short Read Archive under accession number SRP009370 for our analysis. Differentially expressed genes (DEGs) between Ring (R) and early trophozoite (ET), late trophozoite (LT), schizont (Sc), gametocyte stages (GII), gametocyte stages (GV), ookinete (Oo) stages are 2442, 2796, 2935, 2807, 2180, 2895 respectively. There are total 4594 unique DEGs in the samples. DAVID was used to categorize enriched biological themes in the list of DEGs. It can be seen that main functions related to GO term ‘Biological Process’ are antigenic variation, pathogenesis, single organismal cell-cell adhesion, GO term ‘Cellular Component’ are host cell plasma membrane, infected host cell surface knob and GO term ‘Molecular Function’ are cell adhesion molecule binding, ATP-dependent RNA helicase activity. We found that PF3D7_1000400, PF3D7_1000600, PF3D7_0900500, PF3D7_0901500, PF3D7_0937400 were most up regulated and PF3D7_0632800, PF3D7_0711700, PF3D7_0712400, PF3D7_0712600, PF3D7_0712900, PF3D7_0808600 and PF3D7_0808700 were most down regulated genes involved in antigenic variation. Also PF3D7_0930300 was most up-regulated in Sc, LT and Oo stages and PF3D7_0936500 was most up-regulated in GV stage and PF3D7_0632800, PF3D7_0711700, PF3D7_0712400, PF3D7_0712600, PF3D7_0712900, PF3D7_0808600, PF3D7_0808700 were most down regulated genes involved in pathogenesis. A total of 300 pathways were predicted using KAAS server. Majority of the DEGs were found to be associated with important biological pathways such as metabolic pathways, biosynthesis of secondary metabolites, ribosome, spliceosome, biosynthesis of antibiotics, purine metabolism. Citation: Singh, S.K., Malik, A., Firoz, A., Gupta, K.L. and Reddy, M.S. Functional annotation and pathway analysis of genes differentially expressed in different stages of Plasmodium falciparum using RNA-Seq Data [Abstract]. In: Abstracts of the NGBT conference; Oct 02-04, 2017; Bhubaneswar, Odisha, India: Can J Biotech, Volume 1, Special Issue (Supplement), Page 216. https://doi.org/10.24870/cjb.2017-a201

Protein Misfolding and Amyloid Formation in Alzheimer’s Disease

The information necessary for proteins to correctly fold into biologically active three dimensional (3D) structures is present in the amino acid sequence. The ways by which proteins fold still remain one of the unexplained mysteries in the field of protein biochemistry. Investigating the impact and consequences of protein misfolding can help decipher the molecular causes behind the complex amyloid diseases such as Alzheimer’s disease (AD) and Parkinson’s disease. Various participating molecular entities like amyloid beta (Aβ), tau protein, and non-beta sheets are facilitating the pathogenesis of Alzheimer’s disease. Understanding their structure as well as their mechanism of action is useful to decode the therapeutic treatment for these complex diseases.